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Abstract Details

Activity Number: 108
Type: Invited
Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Teaching of Statistics in the Health Sciences
Abstract - #303721
Title: Teaching and Learning Confounding in the Health Sciences
Author(s): Felicity Enders*+ and Miranda Kroehl*+ and Rickey Carter*+ and John McGready*+
Companies: Mayo Clinic and University of Colorado at Denver and Mayo Clinic and The Johns Hopkins University
Address: 200 First Street, SW, Rochester, MN, 55905, 4309 W. 35th Ave, Denver, CO, 80212, 200 First Street, SW, Rochester, MN, 55905, 615 N. Wolfe Street, RM E3543, Baltimore, MD, 21205-2179,
Keywords: statistics education ; confounding ; problem-based learning
Abstract:

In order to read or publish in the medical research literature, students in the health sciences need a thorough understanding of confounding. However, research shows that confounding may be poorly understood by some students even after two courses in biostatistics at the graduate level. We introduce two problem-based guided examples to increase both the breadth and depth of students' understanding of this challenging subject. The first is a visual introduction to confounding and interaction in which students naturally lead the discussion through a set of increasingly complex models. The second example links the analysis to study design and compares results for a t test, a t test performed within the context of regression, and an adjusted analysis termed an "adjusted t test" to help link understanding. We also identify topics for improved teaching for such a challenging subject as confounding, with the goal of removing barriers to student understanding.


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